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76 lines
2.0 KiB
Python
76 lines
2.0 KiB
Python
# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from megatron.core.datasets.megatron_tokenizer import MegatronLegacyTokenizer as MegatronTokenizer
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class NullTokenizer(MegatronTokenizer):
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"""
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Synthetic tokenizer for performance benchmarking and debugging
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Args:
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vocab_size: vocabulary size for embedding
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"""
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def __init__(self, vocab_size):
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super().__init__(None, vocab_size=vocab_size)
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self._vocab_size_without_eod = int(vocab_size)
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self._eod_id = self._vocab_size_without_eod
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def tokenize(self, text):
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return [int(x) for x in text.split(' ')]
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def detokenize(self, ids):
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text = [str(x) for x in ids]
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return ' '.join(text)
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def offsets(self, ids: list[int], text: str) -> list[int]:
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offsets, start_idx = [], 0
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for id_ in ids:
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offsets.append(start_idx)
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start_idx += 1 + len(str(id_))
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return offsets
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@property
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def vocab_size(self):
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return self._vocab_size_without_eod + 1
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@property
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def vocab(self):
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raise NotImplementedError
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@property
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def inv_vocab(self):
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raise NotImplementedError
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@property
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def cls(self):
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return -1
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@property
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def sep(self):
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return -1
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@property
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def mask(self):
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return -1
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@property
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def eod(self):
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return self._eod_id
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@property
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def additional_special_tokens_ids(self):
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return None
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